Wireless backhaul networks are deployed to carry the traffic between a wireless access network and the core network. For example, a wireless backhaul network may comprise a plurality of hubs, each connected to the wired core network, via Ethernet. Each hub serves multiple remote backhaul modules (RBMs), in a point to multipoint or point to point configuration, using a wireless channel. Each RBM is deployed close to an access network base station, such as a small cell base station, and connected to the base station via a cable. The hubs are deployed at the locations where wired high capacity access to the core network is available, e.g. at a fiber point-of-presence.
In a wireless backhaul network, the term cluster refers to a number of RBMs and their respective serving hub. Performance of an RBM such as throughput is contingent upon its received carrier-to-interference-plus-noise ratio (CINR) and the amount of bandwidth allocated to this RBM given a selected carrier. The received signal strength of an RBM is determined by the transmit power of its serving hub and the pathloss between the serving hub and the RBM. The received interference-plus-noise level of an RBM is determined by the transmit powers of all the interfering hubs and the pathlosses between interfering hubs and the RBM. An RBM is affected by an interfering hub when a desired signal and an interfering signal are transmitted over the same carrier frequency.
In orthogonal frequency division multiple access (OFDMA) wireless networks, the frequency resources are divided into subcarriers or tones. In frequency reuse of 1 multi-sector deployment, transmit power optimization can significantly improve the network performance such as throughput, fairness, and coverage in an interference-limited radio environment. Power optimization in a wireless network generally requires the knowledge of channel gains of all radio links. However, in practice, power optimization across the entire network can be computationally complex. To reduce computational complexity, a wireless network is generally partitioned into several neighborhoods, each comprising a subset of hubs, and power optimization is carried out on a per-neighborhood basis.
By way of example, the following references provide background information on known approaches to clustering of nodes in various types of wireless networks:                (1) Lin, C. R.; Gerla, M., “Adaptive clustering for mobile wireless networks”, Selected Areas in Communications, IEEE Journal on, vol. 15, no. 7, pp. 1265-1275, September 1997;        (2) Ameer Ahmed Abbasi, Mohamed Younis, “A survey on clustering algorithms for wireless sensor networks”, Computer Communications, Volume 30, Issues 14-15, 15 Oct. 2007, Pages 2826-2841; and        (3) Geng Chen; Garcia Nocetti, F.; Gonzalez, J. S.; Stojmenovic, I., “Connectivity based k-hop clustering in wireless networks”, System Sciences, 2002, HICSS Proceedings of the 35th Annual Hawaii International Conference on, pp. 2450-2459, 7-10 Jan. 2002.        
In a fixed wireless backhaul network, which is partitioned as described herein, each partition or neighborhood comprises a subset of nodes or hub-RBM clusters, i.e. a subset of one or more hubs and the RBMs served by the subset of hubs. To reduce computational complexity for power optimization, each neighborhood has access only to the channel gains of the RBM-to-hub radio links within the same neighborhood. However, system performance tends to degrade if each partition or neighborhood tries to maximize its sum utility by optimizing its own power levels independently of other partitions or neighborhoods. Employing the same power optimization method independently in each neighborhood will result in higher hub transmit power and hence, poorer overall system performance.
Most of the existing power control schemes in partitioned wireless networks consider a network partitioning boundary in which the performance degradation of power control algorithms due to network partitioning is less than a certain threshold. However, this methodology generally requires a joint power control and network partitioning optimization, which can be computationally expensive. Another method is to apply power control algorithms within a network partition or neighborhood, which do not take into account the effect of in-neighborhood power control on the utilities of RBMs in other neighborhoods, referred to as out-of-neighborhood utilities. In one proposed solution, each hub exchanges their utilities with neighbouring hubs, e.g. via primal-dual decomposition. However, this approach is not scalable. Thus, there is a need for a system and method for power optimization in partitioned wireless backhaul networks which reduces performance degradation relative to known solutions.
An object of the present invention is to provide an improved or alternative method and system for downlink power control in partitioned wireless backhaul networks, particularly for wireless backhaul networks comprising fixed or stationary nodes with directional antennas, including small cell non-line-of-sight (NLOS) backhaul networks.